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Update sumk_dft_transport.py

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Include Raman in transport_distribution
This commit is contained in:
Germán Blesio 2023-10-04 14:36:21 +02:00 committed by Alexander Hampel
parent 0e1e767593
commit 1919aa7ed7
1 changed files with 44 additions and 21 deletions
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python/triqs_dft_tools/sumk_dft_transport.py
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@ -556,7 +556,7 @@ def init_spectroscopy(sum_k, code='wien2k', w90_params={}):
# Uses .data of only GfReFreq objects. # Uses .data of only GfReFreq objects.
def transport_distribution(sum_k, beta, directions=['xx'], energy_window=None, Om_mesh=[0.0], with_Sigma=False, n_om=None, broadening=0.0, code='wien2k'): def transport_distribution(sum_k, beta, directions=['xx'], energy_window=None, Om_mesh=[0.0], with_Sigma=False, n_om=None, broadening=0.0, code='wien2k', mode='optics', raman_options={}):
r""" r"""
Calculates the transport distribution Calculates the transport distribution
@ -589,6 +589,10 @@ def transport_distribution(sum_k, beta, directions=['xx'], energy_window=None, O
Lorentzian broadening. It is necessary to specify the boradening if with_Sigma = False, otherwise this parameter can be set to 0.0. Lorentzian broadening. It is necessary to specify the boradening if with_Sigma = False, otherwise this parameter can be set to 0.0.
code : string code : string
DFT code from which velocities are being read. Options: 'wien2k', 'wannier90' DFT code from which velocities are being read. Options: 'wien2k', 'wannier90'
mode : string
Choose between optical ('optics') or Raman ('raman') transport distribution.
raman_options : dictionary
additional keywords necessary in case mode == 'raman'. Depending on the situation, the allow keys could be 'custom_dir'.
Returns Returns
------- -------
@ -713,28 +717,47 @@ def transport_distribution(sum_k, beta, directions=['xx'], energy_window=None, O
v_i = slice(b_min - sum_k.band_window_optics[isp][ v_i = slice(b_min - sum_k.band_window_optics[isp][
ik, 0], b_max - sum_k.band_window_optics[isp][ik, 0] + 1) ik, 0], b_max - sum_k.band_window_optics[isp][ik, 0] + 1)
# loop over all symmetries if mode in ('optics'):
for R in sum_k.rot_symmetries: # loop over all symmetries
# get transformed velocity under symmetry R for R in sum_k.rot_symmetries:
if code in ('wien2k'): # get transformed velocity under symmetry R
vel_R = copy.deepcopy(sum_k.velocities_k[isp][ik]) if code in ('wien2k'):
elif code in ('wannier90'): vel_R = copy.deepcopy(sum_k.velocities_k[isp][ik])
vel_R = copy.deepcopy(sum_k.velocities_k[ik]) elif code in ('wannier90'):
for nu1 in range(sum_k.band_window_optics[isp][ik, 1] - sum_k.band_window_optics[isp][ik, 0] + 1): vel_R = copy.deepcopy(sum_k.velocities_k[ik])
for nu2 in range(sum_k.band_window_optics[isp][ik, 1] - sum_k.band_window_optics[isp][ik, 0] + 1): for nu1 in range(sum_k.band_window_optics[isp][ik, 1] - sum_k.band_window_optics[isp][ik, 0] + 1):
vel_R[nu1][nu2][:] = numpy.dot( for nu2 in range(sum_k.band_window_optics[isp][ik, 1] - sum_k.band_window_optics[isp][ik, 0] + 1):
R, vel_R[nu1][nu2][:]) vel_R[nu1][nu2][:] = numpy.dot(
R, vel_R[nu1][nu2][:])
# calculate Gamma_w for each direction from the velocities # calculate Gamma_w for each direction from the velocities
# vel_R and the spectral function A_kw # vel_R and the spectral function A_kw
for direction in directions: for direction in directions:
for iw in range(n_om): for iw in range(n_om):
for iq in range(len(temp_Om_mesh)): for iq in range(len(temp_Om_mesh)):
if (iw + iOm_mesh[iq] >= n_om or omega[iw] < -temp_Om_mesh[iq] + energy_window[0] or omega[iw] > temp_Om_mesh[iq] + energy_window[1]): if (iw + iOm_mesh[iq] >= n_om or omega[iw] < -temp_Om_mesh[iq] + energy_window[0] or omega[iw] > temp_Om_mesh[iq] + energy_window[1]):
continue continue
Gamma_w[direction][iq, iw] += (numpy.dot(numpy.dot(numpy.dot(vel_R[v_i, v_i, dir_to_int[direction[0]]], A_kw[isp][A_i, A_i, int(iw + iOm_mesh[iq])]), Gamma_w[direction][iq, iw] += (numpy.dot(numpy.dot(numpy.dot(vel_R[v_i, v_i, dir_to_int[direction[0]]], A_kw[isp][A_i, A_i, int(iw + iOm_mesh[iq])]),
vel_R[v_i, v_i, dir_to_int[direction[1]]]), A_kw[isp][A_i, A_i, iw]).trace().real * sum_k.bz_weights[ik]) vel_R[v_i, v_i, dir_to_int[direction[1]]]), A_kw[isp][A_i, A_i, iw]).trace().real * sum_k.bz_weights[ik])
elif mode in ('raman'):
if code in ('wannier90'):
assert hasattr(sum_k,"inverse_mass"), 'inverse_mass not available in sum_k. Set calc_inverse_mass=True in w90_params.'
elif code in ('wien2k'):
assert 0, 'Raman for wien2k not yet implemented' #ToDo
# loop over all symmetries
for R in sum_k.rot_symmetries:
for direction in directions:
# calculate the raman vertex for each direction
vert = raman_vertex(sum_k, ik, direction, code, isp, raman_options)
for iw in range(n_om):
for iq in range(len(Om_mesh)):
if (iw + iOm_mesh[iq] >= n_om or omega[iw] < -Om_mesh[iq] + energy_window[0] or omega[iw] > Om_mesh[iq] + energy_window[1]):
continue
Gamma_w[direction][iq, iw] += (numpy.dot(numpy.dot(numpy.dot(vert[v_i, v_i], A_kw[isp][A_i, A_i, int(iw + iOm_mesh[iq])]),
vert[v_i, v_i]), A_kw[isp][A_i, A_i, iw]).trace().real * sum_k.bz_weights[ik])
for direction in directions: for direction in directions:
Gamma_w[direction] = (mpi.all_reduce(Gamma_w[direction]) / sum_k.cell_vol / sum_k.n_symmetries) Gamma_w[direction] = (mpi.all_reduce(Gamma_w[direction]) / sum_k.cell_vol / sum_k.n_symmetries)